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Navicat for MongoDB VS AWS Auto Scaling

Compare Navicat for MongoDB VS AWS Auto Scaling and see what are their differences

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Navicat for MongoDB logo Navicat for MongoDB

Navicat for MongoDB gives you a highly effective GUI interface for MongoDB database management, administration and development.

AWS Auto Scaling logo AWS Auto Scaling

Learn how AWS Auto Scaling monitors your applications and automatically adjusts capacity to maintain steady, predictable performance at the lowest possible cost.
  • Navicat for MongoDB Landing page
    Landing page //
    2022-07-24
  • AWS Auto Scaling Landing page
    Landing page //
    2023-02-26

Category Popularity

0-100% (relative to Navicat for MongoDB and AWS Auto Scaling)

Navicat for MongoDB

AWS Auto Scaling

MySQL Tools
100 100%
MySQL Tools
0% 0
Development
14 14%
Development
86% 86
Monitoring Tools
35 35%
Monitoring Tools
65% 65
Diagnostics Software
0 0%
Diagnostics Software
100% 100

User comments

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Social recommendations and mentions

Based on our record, AWS Auto Scaling seems to be more popular. It has been mentiond 11 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Navicat for MongoDB mentions (0)

We have not tracked any mentions of Navicat for MongoDB yet. Tracking of Navicat for MongoDB recommendations started around Mar 2021.

AWS Auto Scaling mentions (11)

  • Building a Greener Cloud: The Role of an Architect for Sustainability in AWS
    AWS Auto-Scaling is a service that automatically adjusts the capacity of an application in response to changing demand. It monitors resource utilization and scales resources up or down as necessary. By using AWS Auto Scaling, businesses can ensure that their applications are always running at optimal performance levels, without wasting resources or energy. - Source: dev.to / about 1 year ago
  • AWS vs Digital Ocean cost comparison in 2022
    Auto scaling lets you scale in/out your servers based on various conditions. So, you could choose to have a minimum capacity as default and let AWS scale it up automatically when needed. You could also schedule the scaling events based on time (For ex: scale to 2x servers during peak times and back to normal during normal hours) There are also other benefits that come with AWS like better eco-system of tools and... - Source: dev.to / over 1 year ago
  • Hidden, absolutely broken, mechanics
    Guys, whats this? Sounds kinda OP if you ask me Https://aws.amazon.com/autoscaling/. Source: about 2 years ago
  • A first impression of AWS App Runner
    AWS Auto Scaling – Makes sure that the application scales based on the number of concurrent requests. - Source: dev.to / over 2 years ago
  • .NET Applications with Linux Containers
    Many customers start their cloud journey with a lift-and-shift approach, running their NTier .NET Framework applications on EC2 without any code changes. It’s common for these deployments to have more than one EC2 Windows instance with an Application Load Balancer (ALB), routing the user requests to one of the EC2 instances. A stateful application can have session affinity (sticky sessions) enabled at the ALB... - Source: dev.to / over 2 years ago
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What are some alternatives?

When comparing Navicat for MongoDB and AWS Auto Scaling, you can also consider the following products

Studio 3T - The perfect match for your MongoDB team

IBM Cloud Bare Metal Servers - IBM Cloud Bare Metal Servers is a single-tenant server management service that provides dedicated servers with maximum performance.

mongo-express - Web-based MongoDB admin interface written with Node.js, Express and Bootstrap3

AWS Deep Learning AMIs - The AWS Deep Learning AMIs provide machine learning practitioners and researchers with the infrastructure and tools to accelerate deep learning in the cloud, at any scale.

MongoDB Compass - The easiest way to explore and manipulate your MongoDB data

Amazon Elastic Inference - Utilities, Application Utilities, and Machine Learning as a Service

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